Neural Network Inspired Design of Highly Active and Durable N-Doped Carbon Interconnected Molybdenum Phosphide for Hydrogen Evolution Reaction
Source abstract
Abstract
Molybdenum phosphide, as a promising electrocatalyst for the hydrogen evolution reaction (HER), its activity suffers from two main limitations: low active surface area and unsatisfactory electrical conductivity. Herein, inspired by the neural network, we construct a novel artificial neural network-like molybdenum phosphide composite (denoted as MoP@NC-MF), using three-dimensional (3D) melamine resin foams as the scaffold. The neural network-like MoP@NC-MF composite consists of carbon-wrapped MoP nanoparticles of abundant active sites as the “neurons” and N-doped carbon as the “axons”. The MoP@NC-MF composite exhibits high electrocatalytic activity and stability for HER with a low overpotential of 125 mV required to achieve a current density of 10 mA cm–2 and a small Tafel slope of 53.0 mV dec–1 under acidic conditions, which is one of the best HER electrocatalysts among the reported single molybdenum phosphide materials. Such a superior performance of the MoP@NC-MF composite is attributed to the unique neural network structure with both abundant MoP active sites to speed the surface reactions and the interconnected carbon “axons” to promptly transfer electrons. Additionally, the 3D network structure facilitates the liquid reactants/gaseous products transporting to/escaping from the reaction centers. Our findings demonstrate that elaborated design of the morphology and the structure can achieve highly efficient electrocatalysts.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Electrocatalysts for Energy Conversion · Fuel Cells and Related Materials · Ammonia Synthesis and Nitrogen Reduction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Nanomaterial & Electrocatalysis Laboratory, College of Materials Science & Engineering, Qingdao University of Science & Technology, Qingdao 266042, P.R. China
Funding
Shandong Province · National Natural Science Foundation of China
References (58)
Show source-provided references
1. 10.1016/j.ijhydene.2015.11.08410.1016/j.ijhydene.2015.11.084 ↗
2. 10.1016/j.ijhydene.2017.02.12310.1016/j.ijhydene.2017.02.123 ↗
3. 10.1021/cs500923c10.1021/cs500923c ↗
4. 10.1039/C4CS00470A10.1039/C4CS00470A ↗
5. 10.1016/j.nanoen.2016.04.01810.1016/j.nanoen.2016.04.018 ↗
6. 10.1039/c1ee01970h10.1039/c1ee01970h ↗
7. 10.1021/cr100232610.1021/cr1002326 ↗
8. 10.1021/jacs.5b0818610.1021/jacs.5b08186 ↗
9. 10.1039/C2EE23513G10.1039/C2EE23513G ↗
10. 10.1002/anie.20130348010.1002/anie.201303480 ↗
11. 10.1002/cssc.20140237210.1002/cssc.201402372 ↗
12. 10.1021/acsami.7b0133310.1021/acsami.7b01333 ↗
13. 10.1039/C4TA06706A10.1039/C4TA06706A ↗
14. 10.1039/C6NR03657K10.1039/C6NR03657K ↗
15. 10.1021/acsaem.7b0019110.1021/acsaem.7b00191 ↗
16. 10.1002/anie.20150437610.1002/anie.201504376 ↗
17. 10.1002/advs.20170060110.1002/advs.201700601 ↗
18. 10.1021/acsami.7b1382210.1021/acsami.7b13822 ↗
19. 10.1039/C5CS00434A10.1039/C5CS00434A ↗
20. 10.1021/acsaem.7b0015110.1021/acsaem.7b00151 ↗
21. 10.1021/acsaem.8b0048910.1021/acsaem.8b00489 ↗
22. 10.1039/C7TA07895A10.1039/C7TA07895A ↗
23. 10.1039/C7CC06660K10.1039/C7CC06660K ↗
24. 10.1002/adma.20160583810.1002/adma.201605838 ↗
25. 10.1021/acsami.8b0006910.1021/acsami.8b00069 ↗
26. 10.1021/cs500412u10.1021/cs500412u ↗
27. 10.1016/j.electacta.2016.11.10410.1016/j.electacta.2016.11.104 ↗
28. 10.1016/j.elecom.2016.09.00710.1016/j.elecom.2016.09.007 ↗
29. 10.1039/C8TA01552J10.1039/C8TA01552J ↗
30. 10.1002/adma.20170415610.1002/adma.201704156 ↗
31. 10.1002/cssc.20140245410.1002/cssc.201402454 ↗
32. 10.1039/C4SC02019G10.1039/C4SC02019G ↗
33. 10.1002/anie.20150141910.1002/anie.201501419 ↗
34. 10.1016/j.molcata.2004.10.02910.1016/j.molcata.2004.10.029 ↗
35. 10.1039/c1ee01488a10.1039/c1ee01488a ↗
36. 10.1016/S0021-9517(03)00086-110.1016/S0021-9517(03)00086-1 ↗
37. 10.1021/cr400020d10.1021/cr400020d ↗
38. 10.1002/adma.20140169210.1002/adma.201401692 ↗
39. 10.1039/C7TA09307A10.1039/C7TA09307A ↗
40. 10.1021/acssuschemeng.8b0052910.1021/acssuschemeng.8b00529 ↗
41. 10.1002/anie.20140957910.1002/anie.201409579 ↗
42. 10.1038/ncomms834310.1038/ncomms8343 ↗
43. 10.1002/adma.20170361410.1002/adma.201703614 ↗
44. 10.1002/adma.20180121110.1002/adma.201801211 ↗
45. 10.1002/adma.20130256910.1002/adma.201302569 ↗
46. 10.1021/acsami.6b0352010.1021/acsami.6b03520 ↗
47. 10.1002/adma.20160112510.1002/adma.201601125 ↗
48. 10.1039/C6TA01855F10.1039/C6TA01855F ↗
49. 10.1002/adfm.20150390710.1002/adfm.201503907 ↗
50. 10.1039/C6TA03458F10.1039/C6TA03458F ↗
51. 10.1002/anie.20130349510.1002/anie.201303495 ↗
52. 10.1039/C6TA06088A10.1039/C6TA06088A ↗
53. 10.1016/j.apcatb.2016.05.02710.1016/j.apcatb.2016.05.027 ↗
54. 10.1016/j.electacta.2017.09.09710.1016/j.electacta.2017.09.097 ↗
55. 10.1039/C6CY02406H10.1039/C6CY02406H ↗
56. 10.1039/C6NR05564H10.1039/C6NR05564H ↗
57. 10.1039/C6CC04220A10.1039/C6CC04220A ↗
58. 10.1002/anie.20140822210.1002/anie.201408222 ↗